Spatiotemporal analysis of urban environment based on the vegetation–impervious surface–soil model

Huadong Guo,Qingni Huang,Zhongchang Sun,Ying Zhang,Xinwu Li

doi:10.1117/1.jrs.8.084597

Abstract

This study explores a spatiotemporal comparative analysis of urban agglomeration, comparing the Greater Toronto and Hamilton Area (GTHA) of Canada and the city of Tianjin in China. The vegetation–impervious surface–soil (V–I–S) model is used to quantify the ecological composition of urban/peri-urban environments with multitemporal Landsat images (3 stages, 18 scenes) and LULC data from 1985 to 2005. The support vector machine algorithm and several knowledge-based methods are applied to get the V–I–S component fractions at high accuracies. The statistical results show that the urban expansion in the GTHA occurred mainly between 1985 and 1999, and only two districts revealed increasing trends for impervious surfaces for the period from 1999 to 2005. In contrast, Tianjin has been experiencing rapid urban sprawl at all stages and this has been accelerating since 1999. The urban growth patterns in the GTHA evolved from a monocentric and dispersed pattern to a polycentric and aggregated pattern, while in Tianjin it changed from monocentric to polycentric. Central Tianjin has become more centralized, while most other municipal areas have developed dispersed patterns. The GTHA also has a higher level of greenery and a more balanced ecological environment than Tianjin. These differences in the two areas may play an important role in urban planning and decision-making in developing countries.

Highlights

Nowadays, cities across the world are spreading into their surrounding landscapes, sucking food, energy, water, and resources from the natural environment and profoundly changing global ecosystems
We could not remove the shade from urban areas in the low-albedo fraction image, this could correspond to impervious surface
This study explores the application of the vegetation–impervious surface–soil (V–I–S) method in large-area urban agglomeration mapping and ecological environment analysis

Summary

Introduction

Cities across the world are spreading into their surrounding landscapes, sucking food, energy, water, and resources from the natural environment and profoundly changing global ecosystems. Urban ecosystems are among the most dramatic manifestations of anthropological impacts on the environment.[1,2] Recent research has shown that urban sprawl and increased land use/land cover change in urban areas have considerable impacts on climate, hydrological, and biogeochemical cycles at various scales.[3,4] it is important to understand clearly the different urban land surface characteristics, their spatial and temporal dynamics, and the corresponding responses to regional and global environment change. Researchers have developed a variety of approaches to distinguish surface cover types and numerous environmental variables through using remote sensing data in urban areas. Ridd[2] presented a concept model to parameterize the biophysical composition of urban environments.

Methods

Results

Discussion

Conclusion